Congestion Management Of Power Transmission Considering Multi-Time Interval Demand Response

Electric power industry market reform has provided a rapid, economy andeffective development opportunity for the electric power industry operation. But newchallenges and difficulties occur to threaten system security and stability at the sametime. With the development of power market and continuous improvement ofcompetition, transmission resource limitation has become more and more serious. Forthe sake of guaranteeing the system in the safe and reliable operation state, theproblem transmission congestion has to be solved effectively.Based on the analysis and summarization of traditional congestion managementsas well as the characteristic of demand side management, the problem is solved fromdemand side which performs significantly at load adjustment and mitigatingcongestion. When the congestion happens, through decreasing load demand, themanagement can be flexible, active, economical, controlled to deal with the difficulteffectively.With rational time-of-use(TOU) power price and the price to compensateconsumers, based on the prince elasticity of the demand a demand response model isbuilt. Using price signal, this model transfers a part of electricity consumption in peakperiod to valley period to implement peak load shifting. Take example of the typicaldaily load parameters, characteristics on load adjusting of demand response model aresimulated and analyzed. Based on the proposed model, a new congestion managementmethod is proposed. By use of nodal marginal price, the load buses participatingcongestion management are chosen in order to reduce scope of demand sideparticipate in congestion manangement, raising economy. According to demandresponse model for multi time intervals the load transferring is performed at chosenbuses, and based on primal-dual interior point method the generation unit output isadjusted to implement congestion management at generation-side and demand-sidesimultaneously. IEEE-30system under congestion condition, generation-side and theproposed method implement congestion management are respectively simulated andcomparison. Results of simulation show that the proposed method can effectivelymitigate congestion, keep prices stable and reduce operating cost.